Satellite remote sensing of particulate matter and air quality assessment over global cities

Pawan Gupta, Sundar A. Christopher, Jun Wang, Robert Gehrig, Yc Lee, Naresh Kumar

Research output: Contribution to journalArticle

340 Citations (Scopus)

Abstract

Using 1 year of aerosol optical thickness (AOT) retrievals from the MODerate resolution Imaging Spectro-radiometer (MODIS) on board NASA's Terra and Aqua satellite along with ground measurements of PM2.5 mass concentration, we assess particulate matter air quality over different locations across the global urban areas spread over 26 locations in Sydney, Delhi, Hong Kong, New York City and Switzerland. An empirical relationship between AOT and PM2.5 mass is obtained and results show that there is an excellent correlation between the bin-averaged daily mean satellite and ground-based values with a linear correlation coefficient of 0.96. Using meteorological and other ancillary datasets, we assess the effects of wind speed, cloud cover, and mixing height (MH) on particulate matter (PM) air quality and conclude that these data are necessary to further apply satellite data for air quality research. Our study clearly demonstrates that satellite-derived AOT is a good surrogate for monitoring PM air quality over the earth. However, our analysis shows that the PM2.5-AOT relationship strongly depends on aerosol concentrations, ambient relative humidity (RH), fractional cloud cover and height of the mixing layer. Highest correlation between MODIS AOT and PM2.5 mass is found under clear sky conditions with less than 40-50% RH and when atmospheric MH ranges from 100 to 200 m. Future remote sensing sensors such as Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) that have the capability to provide vertical distribution of aerosols will further enhance our ability to monitor and forecast air pollution. This study is among the first to examine the relationship between satellite and ground measurements over several global locations.

Original languageEnglish
Pages (from-to)5880-5892
Number of pages13
JournalAtmospheric Environment
Volume40
Issue number30
DOIs
StatePublished - Sep 1 2006
Externally publishedYes

Fingerprint

world city
Air quality
Aerosols
particulate matter
Remote sensing
air quality
Satellites
aerosol
remote sensing
cloud cover
Radiometers
MODIS
relative humidity
Atmospheric humidity
Aqua (satellite)
Terra (satellite)
CALIPSO
Imaging techniques
clear sky
Bins

Keywords

  • Aerosols
  • Air quality
  • Mega cities
  • Satellite remote sensing

ASJC Scopus subject areas

  • Atmospheric Science
  • Environmental Science(all)
  • Pollution

Cite this

Satellite remote sensing of particulate matter and air quality assessment over global cities. / Gupta, Pawan; Christopher, Sundar A.; Wang, Jun; Gehrig, Robert; Lee, Yc; Kumar, Naresh.

In: Atmospheric Environment, Vol. 40, No. 30, 01.09.2006, p. 5880-5892.

Research output: Contribution to journalArticle

Gupta, Pawan ; Christopher, Sundar A. ; Wang, Jun ; Gehrig, Robert ; Lee, Yc ; Kumar, Naresh. / Satellite remote sensing of particulate matter and air quality assessment over global cities. In: Atmospheric Environment. 2006 ; Vol. 40, No. 30. pp. 5880-5892.
@article{18bf0ffefee14266a02788c714191272,
title = "Satellite remote sensing of particulate matter and air quality assessment over global cities",
abstract = "Using 1 year of aerosol optical thickness (AOT) retrievals from the MODerate resolution Imaging Spectro-radiometer (MODIS) on board NASA's Terra and Aqua satellite along with ground measurements of PM2.5 mass concentration, we assess particulate matter air quality over different locations across the global urban areas spread over 26 locations in Sydney, Delhi, Hong Kong, New York City and Switzerland. An empirical relationship between AOT and PM2.5 mass is obtained and results show that there is an excellent correlation between the bin-averaged daily mean satellite and ground-based values with a linear correlation coefficient of 0.96. Using meteorological and other ancillary datasets, we assess the effects of wind speed, cloud cover, and mixing height (MH) on particulate matter (PM) air quality and conclude that these data are necessary to further apply satellite data for air quality research. Our study clearly demonstrates that satellite-derived AOT is a good surrogate for monitoring PM air quality over the earth. However, our analysis shows that the PM2.5-AOT relationship strongly depends on aerosol concentrations, ambient relative humidity (RH), fractional cloud cover and height of the mixing layer. Highest correlation between MODIS AOT and PM2.5 mass is found under clear sky conditions with less than 40-50{\%} RH and when atmospheric MH ranges from 100 to 200 m. Future remote sensing sensors such as Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) that have the capability to provide vertical distribution of aerosols will further enhance our ability to monitor and forecast air pollution. This study is among the first to examine the relationship between satellite and ground measurements over several global locations.",
keywords = "Aerosols, Air quality, Mega cities, Satellite remote sensing",
author = "Pawan Gupta and Christopher, {Sundar A.} and Jun Wang and Robert Gehrig and Yc Lee and Naresh Kumar",
year = "2006",
month = "9",
day = "1",
doi = "10.1016/j.atmosenv.2006.03.016",
language = "English",
volume = "40",
pages = "5880--5892",
journal = "Atmospheric Environment",
issn = "1352-2310",
publisher = "Pergamon Press Ltd.",
number = "30",

}

TY - JOUR

T1 - Satellite remote sensing of particulate matter and air quality assessment over global cities

AU - Gupta, Pawan

AU - Christopher, Sundar A.

AU - Wang, Jun

AU - Gehrig, Robert

AU - Lee, Yc

AU - Kumar, Naresh

PY - 2006/9/1

Y1 - 2006/9/1

N2 - Using 1 year of aerosol optical thickness (AOT) retrievals from the MODerate resolution Imaging Spectro-radiometer (MODIS) on board NASA's Terra and Aqua satellite along with ground measurements of PM2.5 mass concentration, we assess particulate matter air quality over different locations across the global urban areas spread over 26 locations in Sydney, Delhi, Hong Kong, New York City and Switzerland. An empirical relationship between AOT and PM2.5 mass is obtained and results show that there is an excellent correlation between the bin-averaged daily mean satellite and ground-based values with a linear correlation coefficient of 0.96. Using meteorological and other ancillary datasets, we assess the effects of wind speed, cloud cover, and mixing height (MH) on particulate matter (PM) air quality and conclude that these data are necessary to further apply satellite data for air quality research. Our study clearly demonstrates that satellite-derived AOT is a good surrogate for monitoring PM air quality over the earth. However, our analysis shows that the PM2.5-AOT relationship strongly depends on aerosol concentrations, ambient relative humidity (RH), fractional cloud cover and height of the mixing layer. Highest correlation between MODIS AOT and PM2.5 mass is found under clear sky conditions with less than 40-50% RH and when atmospheric MH ranges from 100 to 200 m. Future remote sensing sensors such as Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) that have the capability to provide vertical distribution of aerosols will further enhance our ability to monitor and forecast air pollution. This study is among the first to examine the relationship between satellite and ground measurements over several global locations.

AB - Using 1 year of aerosol optical thickness (AOT) retrievals from the MODerate resolution Imaging Spectro-radiometer (MODIS) on board NASA's Terra and Aqua satellite along with ground measurements of PM2.5 mass concentration, we assess particulate matter air quality over different locations across the global urban areas spread over 26 locations in Sydney, Delhi, Hong Kong, New York City and Switzerland. An empirical relationship between AOT and PM2.5 mass is obtained and results show that there is an excellent correlation between the bin-averaged daily mean satellite and ground-based values with a linear correlation coefficient of 0.96. Using meteorological and other ancillary datasets, we assess the effects of wind speed, cloud cover, and mixing height (MH) on particulate matter (PM) air quality and conclude that these data are necessary to further apply satellite data for air quality research. Our study clearly demonstrates that satellite-derived AOT is a good surrogate for monitoring PM air quality over the earth. However, our analysis shows that the PM2.5-AOT relationship strongly depends on aerosol concentrations, ambient relative humidity (RH), fractional cloud cover and height of the mixing layer. Highest correlation between MODIS AOT and PM2.5 mass is found under clear sky conditions with less than 40-50% RH and when atmospheric MH ranges from 100 to 200 m. Future remote sensing sensors such as Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) that have the capability to provide vertical distribution of aerosols will further enhance our ability to monitor and forecast air pollution. This study is among the first to examine the relationship between satellite and ground measurements over several global locations.

KW - Aerosols

KW - Air quality

KW - Mega cities

KW - Satellite remote sensing

UR - http://www.scopus.com/inward/record.url?scp=33748305652&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33748305652&partnerID=8YFLogxK

U2 - 10.1016/j.atmosenv.2006.03.016

DO - 10.1016/j.atmosenv.2006.03.016

M3 - Article

AN - SCOPUS:33748305652

VL - 40

SP - 5880

EP - 5892

JO - Atmospheric Environment

JF - Atmospheric Environment

SN - 1352-2310

IS - 30

ER -